Threading Language and Support. CS528 Multithreading: Programming with Threads. Programming with Threads

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1 Threading Language and Support CS528 Multithreading: Programming with Threads A Sahu Dept of CSE, IIT Guwahati Pthread: POSIX thread Popular, Initial and Basic one Improved Constructs for threading c++ thread : available in c++11, c++14 Java thread : very good memory model Atomic function, Mutex Thread Pooling and higher level management OpenMP (loop based) Cilk (dynamic DAG based) A Sahu 1 Programming with Threads Threads Shared variables The need for synchronization Synchronizing with semaphores Thread safety and reentrancy Races and deadlocks Traditional View of a Process Process = process context + code, data, and stack Process context Program context: Stack pointer (SP) Program counter (PC) Kernel context: VM structures Descriptor table brk pointer SP brk PC 0 Code, data, and stack stack shared libraries run time heap read/write data read only code/data Alternate View of a Process Process = thread+ code, data & kernel context SP Thread (main thread) stack Thread context: Stack pointer (SP) Program counter (PC) brk PC 0 Code and Data shared libraries run time heap read/write data read only code/data Kernel context: VM structures Descriptor table brk pointer A Process With Multiple Threads Multiple threads can be associated with a process Each thread has its own logical control flow (sequence of PC values) Each thread shares the same code, data, and kernel context Each thread has its own thread id (TID) 1

2 A Process With Multiple Threads Thread 1 (main thread) stack 1 Thread 1 context: SP1 PC1 0 Shared code and data shared libraries run time heap read/write data read only code/data Kernel context: VM structures Descriptor table brk pointer Thread 2 (peer thread) stack 2 Thread 2 context: SP2 PC2 Logical View of Threads Threads associated with a process form a pool of peers Unlike processes, which form a tree hierarchy Threads associated with process foo T2 T1 shared code, data and kernel context T5 T3 T4 Process hierarchy P0 sh P1 sh fooo bar sh Threads vs. Processes How threads and processes are similar Each has its own logical control flow Each can run concurrently Each is context switched Threads vs. Processes How threads and processes are different Threads share code and data, processes (typically) do not Threads are somewhat less expensive than processes Process control (creating and reaping) is twice as expensive as thread control Linux/Pentium IV numbers: ~20K cycles to create and reap a process ~10K cycles to create and reap a thread Posix Threads (Pthreads) Interface Creating and reaping threads pthread_create, pthread_join Determining your thread ID : pthread_self Terminating threads pthread _ cancel, pthread _ exit exit [terminates all threads], return [terminates current thread] Synchronizing access to shared variables pthread_mutex_init, pthread_mutex_[un]lock pthread_cond_init, pthread_cond_[timed]wait The Pthreads "hello, world" Program /* thread routine */ void *HelloW(void *vargp) { printf("hello, world!\n"); return NULL; Thread attributes (usually NULL) Thread argument int main() { (void *p) pthread_t tid; pthread_create(&tid, NULL, Hellow, NULL); pthread_join(tid, NULL); return value (void **p) 2

3 Execution of Threaded hello, world call Pthread_create() Pthread_create() returns call Pthread_join() main thread waits for peer thread to terminate Pthread_join() returns exit() terminates main thread and any peer threads main thread peer thread printf() return NULL; (peer thread terminates) Pros and Cons: Thread Based Designs + Easy to share data structures between threads E.g., logging information, file cache + Threads are more efficient than processes Unintentional sharing can introduce subtle and hard to reproduce errors! Ease of data sharing is greatest strength of threads Also greatest weakness! VectorSum Serial int A[VSize], B[VSize], C[VSize]; void VectorSumSerial(){ for( int j=0;j<size;j++) A[j]=B[j]+C[j]; VectorSum Parallel for (i=0;i<100;i++) Serial (1 Thread) T1 T2 T3 T4 0 24,25 49,50 74,75 99 Independent Divide work into equal for each thread Work per thread: Size/numThread VectorSum Parallel void *DoVectorSum(void *tid){ int j, SzPerthrd, LB, UB, TID; TID= *((int *)tid); SzPerthrd=(VSize/NUM_THREADS); LB= SzPerthrd*TID;UB=LB+SzPerthrd; P d for(j=lb;j<ub;j++) A[j]=B[j]+C[j]; VectorSum Parallel int main(){ int i; pthread_t thread[num_threads]; for (i = 0; i < NUM_THREADS; i++) pthread_create(&thread[i], NULL, DoVectorSum, (void*)&i); for (i = 0; i < NUM_THREADS; i++) pthread_join(thread[i], NULL); 3

4 Matrix multiply and threaded matrix multiply Matrix multiply: C = A B N C [ i, j] = A[ i, k] B[ k, j] k = 1 Divide the whole rows to T chunks Each chunk contains : N/T rows, Assume N%T=0 Matrix multiply Serial void MatMul(){ int i,j,k,s; for(i=0;i<size;i++) for(j=0;j<size;j++){ S=0; for(k=0;k<size;k++) S=S+A[i][k]*B[k][j]; C[i][j]=S; Matrixmul Parallel for (row=0;row<size;row++) C[row][0:col]= Serial (1 Thread) T1 T2 T3 T4 0 SIZE/4 SIZE/2 SIZE*3/4 99 Matrix Pthreaded: RowWise void * DoMatMulThread(void *arg){ int i,j,k,s,lb,ub, TID, ThrdSz; TID=*((int *)arg);thrdsz=size/numthrd; LB=TID*ThrdSz;UB=LB+ThrdSz; for(i=lb;i<ub;i++) for(j=0;j<size;j++){ 0 j<si j++){ S=0; for(k=0;k<size;k++) S=S+A[i][k]*B[k][j]; C[i][j]=S; Matrix Pthreaded: RowWise int main(){ pthread_t thread[numthread]; int t; Initialize(); pthread_create(&thread[t], NULL, DoMatMulThread, &t); pthread_join(thread[t], NULL); TestResult(); Estimating π using Monte Carlo The probability of a random point lying inside the unit circle: If pick a random point N times and M of those times the point lies inside the unit circle: If N becomes very large, P=P 0 N M (x,y) 4

5 Value of PI: Monte Carlo Method void MontePI(){ int count=0,i; double x,y,z; for ( i=0; i<niter; i++) { x = (double)rand()/rand () _ MAX; y = (double)rand()/rand_max; z = x*x+y*y; if (z<=1) count++; pi=(double)count/niter*4; Value of PI: Pthreaded int main(){ pthread_t thread[numthread]; double pi; int t, at[numthread], count, TotalIter; pthread_create(&thread[t], NULL, DoLocalMC_PI, &t); pthread_join(thread[t], NULL); for(t=0;t<numthread;t++) count+=lcount[t]; TotalIter=niter*NumThread; pi=((double)count/totaliter)*4; Value of PI: Pthreaded int LCount[NumThread]; void *DoLocalMC_PI(void *atid){ int tid, count, i; double x,y,z; tid= *((int *)atid); count=0;lcount[tid]=0; for ( i=0; i<niter; i++) { x = (double)rand()/rand_max; y = (double)rand()/rand_max; z = x*x+y*y; if (z<=1) count++; LCount[tid]=count; What is the sieve of Eratosthenes? Used to find prime number between 2 and N It works by gradually eliminating multiple of smallest unmark prime (x) in the given interval Till x 2 > N Sieve of Eratosthenes Current Prime 2 [2,3,4,5,6,7,8,9,10,11,12,13, 14,15,16,17,18,19,20] Current Prime 2 [2,3,4,5, 6,7,8,9,10,11,12,13,14,15,16,17,18,19,20] Current Prime 3 List : [2, 3, 5, 7, 9, 11, 13, 15, 17, 19] Current Prime 3 List : [2, 3, 5, 7, 9, 11,13,15, 17,19] Current Prime 5 and 5< ceil(sqrt(20)) List : [2, 3, 5, 7, 11, 13, 17,19] //All are primes Sieve of Eratosthenes int prime[maxnum], CurrPrime; void DoStriking(){ for(int i=2*currprime;i<maxnum; i=i+currprime) prime[i]=0; int main() { int i, sqrtmaxnum=sqrt(maxnum)+1; for(i=0;i<maxnum;i++) prime[i]=1; for(i=2;i<sqrtmaxnum;i++){ if (prime[i]==0) continue ; CurrentPrime=i; DoStriking(); 5

6 Sieve of Eratosthenes: Pthreaded void *DoStriking(void *tid){ int i, sizeperthrd, LB, UB; int TID= *((int *)tid); sizeperthrd=(maxnum/num_threads); LB=sizeperthrd*TID; UB=LB+sizeperthrd; if(lb<(2*currprime))lb=2*currprime; for(i=lb;i<ub;i=i+currprime) prime[i]=0; Sieve of Eratosthenes: Pthreaded for(i=2;i<sqrtmaxnum;i++){ if (prime[i]==0) continue ; CurrPrime=i; for (j = 0; j < NUM_THREADS; j++) th d t ( th d[j] pthread_create(&thread[j], NULL, DoStriking, (void*)&j); for (j = 0; j < NUM_THREADS; j++) pthread_join(thread[j],null); 6

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